The most common modes of diagnostic ultrasound imaging include B- and M-modes (used to image internal, physical structure), Doppler, and color flow (primarily used to image flow characteristics, such as in blood vessels). Color flow mode is typically used to detect the velocity of blood flow toward/away from the transducer, and it essentially utilizes the same technique as is used in Doppler mode. Whereas Doppler mode displays velocity versus time for a single selected sample volume, color flow mode displays hundreds of adjacent sample volumes simultaneously, all laid over a B-mode image and color-coded to represent each sample volume's velocity.
Measurement of blood flow in the heart and vessels using the Doppler effect is well known. Whereas the amplitude of the reflected waves is employed to produce black and white images of the tissues, the frequency shift of backscattered waves may be used to measure the velocity of the backscatterers from tissue or blood. The change or shift in backscattered frequency increases when blood flows toward the transducer and decreases when blood flows away from the transducer. Color flow images are produced by superimposing a color image of the velocity of moving material, such as blood, over the black and white anatomical image. The measured velocity of flow at each pixel determines its color.
A major difficulty in making Doppler effect measurements of reflected ultrasonic waves from blood is that the received echo signal typically contains a large component produced by stationary or slowly moving tissues, whereas blood reflects ultrasound very weakly. The stationary tissues do not produce any frequency shift in the reflected waves and these components can easily be filtered out without affecting the flow measurement. However, the reflections produced by the moving tissue due to cardiac or respiratory motion are frequency shifted and may completely overwhelm signals from slowly flowing blood.
In standard color flow processing, a high pass filter known as a wall filter is applied to the data before a color flow estimate is made. The purpose of this filter is to remove signal components produced by tissue surrounding the blood flow of interest. If these signal components are not removed, the resulting velocity estimate will be a combination of the velocities from the blood flow and the surrounding tissue. The backscatter component from tissue is many times larger than that from blood, so the velocity estimate will most likely be more representative of the tissue, rather than the blood flow. In order to get the flow velocity, the tissue signal must be filtered out.
When a high-flow-velocity area (such as a blood vessel) is imaged in color flow mode, each of the sample volumes has a frequency response similar to that of FIG. 3A. The region of high amplitude centered around the zero frequency represents the presence of some fairly non-moving structure (typically a blood vessel wall), while the region of somewhat less amplitude centered around some relatively high frequency represents the presence of high flow velocity (typically blood flow). Because of the large difference in frequency between the non-moving structure and the fast-moving blood flow, it is very easy to use a "wall filter" as shown in FIG. 3A to produce the output shown in FIG. 3B, where the portion of the frequency response corresponding to the non-moving wall has been eliminated. After such wall filtering, some scheme of determining the maximum remaining amplitude (i.e., that of the high-velocity blood flow) can be utilized so that the flow velocity for that particular sample volume can be displayed.
However, a problem arises in applying wall filtering in low-flow-velocity imaging. FIG. 4A shows a typical frequency response for a sample volume in a low-flow-velocity region. Since the frequencies of the non-moving wall and the slow-moving flow are close together, it is difficult to effectively apply a wall filter to eliminate the "wall" response without resulting in a distorted slow-flow response portion (see FIG. 4B).
Most commonly, color flow processors assume that the large signal returning from the surrounding tissue is static, that is the tissue is not moving. If this is the case, the in-phase and quadrature I and Q data can be filtered separately with simple real filters which remove the DC component and very low frequencies. The cutoff frequency of these high pass filters can be varied for a given application by changing the filter coefficients.
The assumption of static tissue is generally a good one for radiology applications, except in the abdomen, where residual respiratory and cardiac motion cause some amount of tissue motion. In addition, the motion of the handheld transducer will also look like tissue motion. Since the velocity of this motion is usually slow compared to the velocity of the blood flow being imaged, the operator can set the wall filter cutoff frequency high enough to filter out the tissue signal component. Filtering in this way, however, will also remove signals from low-velocity blood flow, which are often the signals that the operator wants to image.
Some prior art systems provide a wall filter which is manually adjusted by the operator to filter out a narrow band of frequencies in the echo signal centered on the carrier frequency where static signals lie. The operator must adjust the bandwidth of this filter so that the reflected signals from the slow moving wall are eliminated without distorting the measurement of blood flow. If the filter bandwidth is set too wide, signals from slowly moving blood may be eliminated. In addition, the filter setting is static and is applied over the whole image. As a result, the filter may work adequately at some locations in the field of view of the image, but not at other locations.
The processing approach described in U.S. patent application Ser. No. 08/001,998 uses adaptive wall filtering, which is performed by mixing the wall signal down to zero frequency and then removing the wall signal using a real time domain filter to filter the I data and the Q data. This reduces the amplitude of the wall signal and allows the flow signal to be detected with greater accuracy, and at lower velocities than without this method. The adaptive wall filter automatically adjusts its center frequency and bandwidth as a function of the received echo signal. A complex mixer receives the received echo signal and outputs a modified echo signal which is shifted in frequency by an amount which is equal to and opposite to the mean frequency of the received echo signal. The wall filter receives the modified echo signal and filters out a band of frequencies determined by the variance of the received echo signal. By automatically shifting the frequency of the received echo signal by an amount opposite to its measured mean frequency, the signal components therein due to slowly moving tissue are effectively shifted to the center of the filter. By automatically controlling the width of the stop band of the filter in dependence on the measured variance, the signal components produced by slowly moving tissue are filtered out. The filter output is then processed in a conventional manner to produce a color signal indicative of flow velocity.